ArticleJournal of general internal medicine2023
Cluster Analysis of the Highest Users of Medical, Behavioral Health, and Social Services in San Francisco.
Article in Journal of general internal medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
7 citing papers in PubMed, 14 citations in OpenAlex.
- The ELEVATE Maternal Health Center of Excellence: A Program to Reduce Maternal Morbidity From Substance Use Disorder in Utah.Substance use & addiction journal · 2026Article
- "Majority of the time, I know I'm right": understanding the decisions behind persistently high ED utilization among patients with substance use disorders.BMC health services research · 2025Article
- Homelessness Following Jail Exit Among Previously Housed Individuals.Journal of urban health : bulletin of the New York Academy of Medicine · 2025Article
- Is frequent emergency department use a complement or substitute for other healthcare services? Evidence from South Carolina Medicaid enrollees.Health services research · 2025Article
- Association of housing status and cancer diagnosis, care coordination and outcomes in a public hospital: a retrospective cohort study.BMJ open · 2024Article
- Emergency Department Use among Patients with Mental Health Problems: Profiles, Correlates, and Outcomes.International journal of environmental research and public health · 2024Article
- A scoping review of the clinical application of machine learning in data-driven population segmentation analysis.Journal of the American Medical Informatics Association : JAMIA · 2023Article
Corrections and comments
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Authors and funding
7 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundIn the City and County of San Francisco, frequent users of emergent and urgent services across different settings (i.e., medical, mental health (MH), substance use disorder (SUD) services) are referred to as high users of multiple systems (HUMS). While often grouped together, frequent users of the health care system are likely a heterogenous population composed of subgroups with differential management needs.
objectiveTo identify subgroups within this HUMS population using a cluster analysis.
designCross-sectional study of HUMS patients for the 2019-2020 fiscal year using the Coordinated Care Management System (CCMS), San Francisco Department of Public Health's integrated data system.
participantsWe calculated use scores based on nine types of urgent and emergent medical, MH, and SUD services and identified the top 5% of HUMS patients. Through k-medoids cluster analysis, we identified subgroups of HUMS patients. MAIN MEASURES: Subgroup-specific demographic, comorbidity, and service use profiles. KEY
resultsThe top 5% of HUMS patients in the study period included 2657 individuals; 69.7% identified as men and 66.5% identified as non-White. We detected 5 subgroups: subgroup 1 (N = 298, 11.2%) who were relatively younger with prevalent MH and SUD comorbidities, and MH services use; subgroup 2 (N = 478, 18.0%), who were experiencing homelessness, with multiple comorbidities, and frequent use of medical services; subgroup 3 (N = 449, 16.9%), who disproportionately self-identified as Black, with prolonged homelessness, multiple comorbidities, and persistent HUMS status; subgroup 4 (N = 690, 26.0%), who were relatively older, disproportionately self-identified as Black, with prior homelessness, multiple comorbidities, and frequent use of medical services; and subgroup 5 (N=742, 27.9%), who disproportionately self-identified as Latinx, were housed, with medical comorbidities and frequent medical service use.
conclusionsOur study highlights the heterogeneity of HUMS patients. Interventions must be tailored to meet the needs of these diverse patient subgroups.
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